Human–machine knowledge building: reconceptualising knowledge building partnerships in the age of artificial intelligence.
Saved in:
| Title: | Human–machine knowledge building: reconceptualising knowledge building partnerships in the age of artificial intelligence. |
|---|---|
| Authors: | Falloon, Garry (AUTHOR), Jones, Mellita (AUTHOR) |
| Source: | Educational Technology Research & Development. Jun2026, Vol. 74 Issue 3, p1653-1668. 16p. |
| Subjects: | Generative artificial intelligence, Division of labor, Bloom's taxonomy, Collaborative learning, Discourse, Human-computer interaction, Information sharing |
| Abstract: | Increasingly ubiquitous access to Generative Artificial Intelligence (GenAI) presents many challenges, but also opportunities. The fundamental capacity of GenAI to mimic and augment human cognitive functioning, sets it aside from the myriad of previous technological 'cognitive tool' innovations that have been promoted as supporting human thinking, problem solving and knowledge construction. Indeed, GenAI has the potential to play a far more substantive and interactive role in knowledge building, founded on real-time dialogic discourse between humans and GenAI working in symbiotic knowledge building partnerships. This article draws on Scardamalia and Bereiter's early work on human knowledge building communities and Krathwohl's revision of Bloom's Cognitive Domain, reconceptualising these to theorise how humans and GenAI might partner in processes of collaborative, joint knowledge construction. It presents a unique model identifying three flexible 'Zones', representing different but overlapping components of knowledge building, aligned with Bloom's cognitive dimensions. It identifies a possible 'division of labour' within and across Zones, but argues the primacy of innately human capabilities operating in the Judgement Zone, as crucial to reasoned decision making and accurate knowledge building. The model and its discussion provide new insights into how human-GenAI knowledge building partnerships might be established and sustained. [ABSTRACT FROM AUTHOR] |
| Copyright of Educational Technology Research & Development is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: pbh DbLabel: Psychology and Behavioral Sciences Collection An: 195149943 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Human–machine knowledge building: reconceptualising knowledge building partnerships in the age of artificial intelligence. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Falloon%2C+Garry%22">Falloon, Garry</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jones%2C+Mellita%22">Jones, Mellita</searchLink> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Educational+Technology+Research+%26+Development%22">Educational Technology Research & Development</searchLink>. Jun2026, Vol. 74 Issue 3, p1653-1668. 16p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Generative+artificial+intelligence%22">Generative artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Division+of+labor%22">Division of labor</searchLink><br /><searchLink fieldCode="DE" term="%22Bloom's+taxonomy%22">Bloom's taxonomy</searchLink><br /><searchLink fieldCode="DE" term="%22Collaborative+learning%22">Collaborative learning</searchLink><br /><searchLink fieldCode="DE" term="%22Discourse%22">Discourse</searchLink><br /><searchLink fieldCode="DE" term="%22Human-computer+interaction%22">Human-computer interaction</searchLink><br /><searchLink fieldCode="DE" term="%22Information+sharing%22">Information sharing</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Increasingly ubiquitous access to Generative Artificial Intelligence (GenAI) presents many challenges, but also opportunities. The fundamental capacity of GenAI to mimic and augment human cognitive functioning, sets it aside from the myriad of previous technological 'cognitive tool' innovations that have been promoted as supporting human thinking, problem solving and knowledge construction. Indeed, GenAI has the potential to play a far more substantive and interactive role in knowledge building, founded on real-time dialogic discourse between humans and GenAI working in symbiotic knowledge building partnerships. This article draws on Scardamalia and Bereiter's early work on human knowledge building communities and Krathwohl's revision of Bloom's Cognitive Domain, reconceptualising these to theorise how humans and GenAI might partner in processes of collaborative, joint knowledge construction. It presents a unique model identifying three flexible 'Zones', representing different but overlapping components of knowledge building, aligned with Bloom's cognitive dimensions. It identifies a possible 'division of labour' within and across Zones, but argues the primacy of innately human capabilities operating in the Judgement Zone, as crucial to reasoned decision making and accurate knowledge building. The model and its discussion provide new insights into how human-GenAI knowledge building partnerships might be established and sustained. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Educational Technology Research & Development is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=195149943 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11423-026-10605-2 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 16 StartPage: 1653 Subjects: – SubjectFull: Generative artificial intelligence Type: general – SubjectFull: Division of labor Type: general – SubjectFull: Bloom's taxonomy Type: general – SubjectFull: Collaborative learning Type: general – SubjectFull: Discourse Type: general – SubjectFull: Human-computer interaction Type: general – SubjectFull: Information sharing Type: general Titles: – TitleFull: Human–machine knowledge building: reconceptualising knowledge building partnerships in the age of artificial intelligence. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Falloon, Garry – PersonEntity: Name: NameFull: Jones, Mellita IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 10421629 Numbering: – Type: volume Value: 74 – Type: issue Value: 3 Titles: – TitleFull: Educational Technology Research & Development Type: main |
| ResultId | 1 |
